Tese
Sistema de apoio à decisão em tecnologia de aplicação de precisão (SISD-TAP) para a otimização da gestão de pragas nas culturas
Fecha
2014-02-24Registro en:
FERRER, Pablo Gustavo Silva. DECISION SUPPORT SYSTEM FOR PRECISION APPLICATION TECHNOLOGY (SISD-TAP) FOR OPTIMIZING THE MANAGEMENT OF PESTS IN CROPS. 2014. 174 f. Tese (Doutorado em Engenharia Agrícola) - Universidade Federal de Santa Maria, Santa Maria, 2014.
Autor
Ferrer, Pablo Gustavo Silva
Institución
Resumen
Due to the large number and complexity of factors influencing the study of efficiency and efficacy of pesticide application technology, it becomes difficult to develop multivariate methods, to define indicators of interdisciplinary and integrative manner, to control phytosanitary crops. This work conducted with the objective to develop a Decision Support System in Precision Application Technology (SISD-TAP). Which can form simple, practical and effective, providing alternatives and / or scenarios: Normalized (application volume Producer DPRD, Q1), Efficient Biologically (application volume biologically Efficient (DBE, Q2) and Climate / Target (application volume critical DCR, Q3) to the farmer for management control of pests and diseases in your crops. Based on criteria of sustainability and leveraging the vast amounts of information from various surveys and tactical models developed over more than five decades of research in the area of pest management and application technology. The SISD-TAP (Alpha version), allows the analysis of factors associated with cultivation, agro climate, pests, machines and equipment, technology implementation and environmental aspects socioeconomic, to decide on: (1) When is the best time of the application, (2) What are your operational parameters, (3) the efficiency of application requirements and (4) Which will be the implementation costs and environmental hazards expected. Directed with the purpose to enable the optimization of pest control, and promote the adoption of modern management of agribusiness (precision farming and/or management specific sites), with the use of innovative agricultural mechanization (for example systems intelligent sensors and robotics) in order to improve in production.